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This paper presents a recommendation system with a coordinator agent that is adaptive to its environment. Recommendation systems that suggest items to users are gaining popularity in the field of electronic commerce. Various methods such as collaborative, content-based, and demographic recommendation have been used to analyze and predict the preference of users. According to the characteristic of the application domain, the performance of each method varies. In the proposed system, we introduce a coordinator agent that adaptively changes the weights of each recommendation method to provide combined recommendation appropriate for the given environment.